Object-oriented image coding scheme based on DWT and Markov random field

Lei Zheng; Hsien-Hsun Steven Wu; Jyh-Charn S. Liu; Andrew K. Chan

doi:10.1117/12.333825

14 December 1998 Object-oriented image coding scheme based on DWT and Markov random field

Lei Zheng, Hsien-Hsun Steven Wu, Jyh-Charn S. Liu, Andrew K. Chan

Proceedings Volume 3654, Multimedia Computing and Networking 1999; (1998) https://doi.org/10.1117/12.333825
Event: Electronic Imaging '99, 1999, San Jose, CA, United States

Abstract

In this paper, we introduce an object-oriented image coding algorithm to differentiate regions of interest (ROI) in visual communications. Our scheme is motivated by the fact that in visual communications, image contents (objects) are not equally important. For a given network bandwidth budget, one should give the highest transmission priority to the most interesting object, and serve the remaining ones at lower priorities. We propose a DWT based Multiresolution Markov Random Field technique to segment image objects according to their textures. We show that this technique can effectively distinguish visual objects and assign them different priorities. This scheme can be integrated with our ROI compression coder, the Generalized Self-Similarity Tress codex, for networking applications.

Citation Download Citation

Lei Zheng, Hsien-Hsun Steven Wu, Jyh-Charn S. Liu, and Andrew K. Chan "Object-oriented image coding scheme based on DWT and Markov random field", Proc. SPIE 3654, Multimedia Computing and Networking 1999, (14 December 1998); https://doi.org/10.1117/12.333825

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available